Strelen Artificial Intelligence

Bringing artificial intelligence and industrial automatization together!

About us

Strelen GmbH is a system house specializing in AI-applications in industrial automation. We develop solutions to tasks related to identification, classification, quality control, and control technology. You can find our successfully implemented projects on our “References” page. Our headquarters are in Kreuzlingen (Switzerland), with a branch in the Frankfurt area (Germany) and we are mainly active in the DACH area. But our solutions can also be found all over Europe, America, and Asia.

In addition to developing tailor-made solutions for our customers, we offer consultation and feasibility studies in regard to specific questions. Please use our contact form to ask for our assistance or send us an email.

Our Services

Implementing Customized AI and ML Solutions

We develop and implement individual solutions for our customers in the areas

            Predictive maintenance

            Control technology

            Identifying products or components

Simply tell us about your needs in our contact form or send us an email.

Consulting and Feasibility Studies

A multitude of questions arise before implementing an AI or ML project:

  • Is your task suited for AI or ML procedures?
  • There are numerous AI-procedures such as neural networks, deep learning, nearest-neighbor-method, classic AI procedures, genetic and evolutionary algorithms or hybrid procedures. Which of these procedures offers the best chances of successful implementation for your specific requirements?
  • How should learning patterns be provided? How many learning patterns can be expected?
  • What tools are available for implementation?
  • How much work will be involved?

We offer consulting services for these and other questions, which need to be answered in the run-up to the implementation of a project. Consultations often lead to conducting specific feasibility studies. Are you interested? Please use our contact form to get in touch with us or give us a call.

Our References

Here are some examples of successfully implemented projects:

Incoming goods inspection (product identification)

In the incoming goods department, products are identified on the basis of photos in order to avoid mix-ups. The fully automated solution works reliably and quickly, while the human controls were error-prone and led to expensive complaints.

The solution developed by Strelen is used in the furniture industry. A transfer to other industries is possible.

  • Implemented in the furniture industry

Process control bulk material

A process developed by Strelen controls the dosage of bulk materials in numerous installations around the globe. This stochastic and time-varying process presented plant operators with great challenges due to the frequently fluctuating conditions. By using the Strelen solution, the process is controlled safely, faster and more stable, raw materials are saved, and the number of system interventions by the operators is significantly reduced.

Implemented in the following industries:

  • Food
  • Chemistry
  • Plastic
  • Rubber

Assessing the Quality of Food Products

In the case of food, as with other natural products, quality assessment is associated with particular challenges. While the quality of plastic or metal components can often be determined by measuring, counting or evaluating color, this is not so easy with food. It is not uncommon for an expert’s eye to be able to distinguish between good and less good samples seemingly effortlessly, but without being able to describe exactly what his assessment is based on. This has led Strelen to implement solutions in which intelligent procedures learn from expert assessments and apply the assessment criteria without having to be able to describe them exactly. These methods have been used to evaluate bakery products, confectionery, meat, and sausages.

  • Implemented in the food industry

Cropping Objects (Image Processing)

When taking pictures of bulk material or product conglomerates, it is often a challenge to distinguish the foreground from the background and to reliably separate it in the image. This problem must, for example, be solved in the food assessment before a quality assessment can be carried out. Deep learning methods have proven to be very helpful in this case, in order to cut out the background from an image before a quality assessment is carried out.

  • Implemented in the food industry

Predictive Maintenance

Predictive maintenance uses measurement data such as acoustic signals or vibration data to determine whether conditions in a machine are changing. This makes the detection of imminent faults possible in good time, i.e. before they actually occur.

The powerful predictive maintenance solution developed by Strelen requires significantly less learning input than most other machine learning methods in this field.

  • Implemented in machine and plant construction

Quality Assessment of Foams and Particles

A solution developed by our sister company takes samples of foams or particles and obtains statistical quality indicators from them. The Strelen solution is then able to carry out a quality assessment using AI. The system has learned the criteria for assessment from examples classified by a human expert.

Implemented in the following industries:

  • Food
  • Chemistry
  • Plastics
  • Cosmetics
  • Pharmaceuticals

Contact Us

Thank you for your interest in Strelen AI

Please let us know how we can help you.